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  • University of Nigeria, Nsukka
  • Nigeria
  • 06:34 (UTC +01:00)

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Onome-Joseph/README.md

👋 Hello, I'm Onome Joseph Oshevire!

Pronouns : He/Him

About Me

🌟 I’m a data scientist with expert-level knowledge in data science and machine learning deployment.
🚀 My goal is to build impactful systems that leverage predictive analytics, recommendations, and natural language processing to solve real-world problems.
🤝 I’m looking to collaborate with frontend developers to design interactive and user-friendly interfaces for data-driven applications.

What I’m Working On

  • Created and still creating systems that deliver monetary value to businesses.
  • Exploring ways to make machine learning models accessible to end-users for problem solving.
  • Learning and growing every day in the fields of data science and Artificial intelligence.

Fun Fact

💡 I once used machine learning to predict whether I’d finish a series based on its genre and my circumstances.

Let’s Connect!

📧 Email: [onomejoseph2341@gmail.com] 📱 WhatsApp: [+234 8124566941]

Feel free to reach out for collaborations, brainstorming sessions, or just to say hi!

Popular repositories Loading

  1. ML-Sales-Prediction ML-Sales-Prediction Public

    This repository contains a Sales Prediction Machine Learning Model built to predict sales from a set of features with very high accuracy

    Jupyter Notebook 1

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    This project implements a Flight Price and Duration Prediction Machine Learning Model. Built to predict both flight price and duration due to their interrelated nature.

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  3. NBA-match-prediction NBA-match-prediction Public

    The model predicts whether a team will win or lose based on player performance statistics from the 2024/25 NBA season.

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  4. Recommender-system-for-Games Recommender-system-for-Games Public

    This project is designed to suggest games to users based on the games they recently played. By leveraging a correlation-based algorithm, the system identifies and recommends games that align with t…

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  5. Song-Recommender-system Song-Recommender-system Public

    This project is designed to suggest songs to users based on their listening habits. Using K-means clustering, the system groups songs by their attributes and recommends songs that align with the us…

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  6. Heart-Attack-Prediction Heart-Attack-Prediction Public

    This project estimates the likelihood of a heart attack for a patient based on their health parameters. The model uses the Random Forest algorithm and achieves very high accuracy.

    Jupyter Notebook 1